Our review
This template provides a standardized structure for creating hands-on exercises in a Physical AI textbook, with sections like objectives, instructions, verification, and challenges.
Strengths
- Clear and reproducible exercise format, reducing writing effort.
- Includes varied exercise types: thought experiments, simulations, hardware integration.
- Offers a difficulty progression aligned with textbook chapters.
- Ensures explicit validation criteria and realistic time estimates.
Limitations
- Specific to the Physical AI textbook and technologies like ROS 2, Jetson, RealSense.
- May need adjustments for other domains or tools.
- Does not cover background content creation, only exercise structure.
Use this template when you need to design a standardized hands-on exercise for a technical textbook on robotics or physical AI.
Avoid this template if you are writing theoretical content without a practical component or if you are working in a very different field from robotics.
Security analysis
SafeThe skill contains only a template for educational exercises with benign ROS 2 commands. No destructive, exfiltrating, or obfuscated actions are present.
No concerns found
Examples
Create an exercise for Chapter 4 of the Physical AI textbook using the exercise-patterns skill. The exercise should be intermediate difficulty, about 30 minutes, and involve creating a ROS 2 publisher node that publishes joint states for a virtual robot arm.Use the exercise-patterns skill to outline a hardware integration exercise for Chapter 12. The student should deploy a ROS 2 node to a Jetson Orin Nano to read RealSense depth data and visualize it on a workstation. Include validation steps and a challenge to stream over Wi-Fi.Using the exercise-patterns skill, generate a thought experiment exercise for Chapter 1. Ask students to list five tasks that require physical embodiment which an LLM alone cannot accomplish. Include a difficulty of beginner and a time estimate of 15 minutes.name: exercise-patterns description: Structure for creating hands-on exercises in the Physical AI textbook.
Exercise Template (Strict Format)
## Exercise X.Y: [Title]
**Difficulty**: [Beginner | Intermediate | Advanced]
**Time**: [15 min | 30 min | 1 hour | 2 hours]
**Hardware**: [Workstation | Jetson + RealSense | Unitree Robot]
### Objectives
By completing this exercise, you will:
- [Action verb] [specific skill] (e.g., "Create a ROS 2 publisher node")
- [Action verb] [specific skill] (e.g., "Visualize sensor data in RViz2")
- [Action verb] [specific skill] (e.g., "Deploy code to Jetson Orin Nano")
### Prerequisites
- Chapter X completed
- ROS 2 Humble installed
- [Specific hardware setup, e.g., "RealSense D435i connected"]
### Instructions
#### Step 1: [Action]
```bash
# Command to run
ros2 pkg create my_package --build-type ament_python
Expected Output:
Successfully created package 'my_package'
Step 2: [Action]
[Detailed instructions with code snippets]
Step 3: [Verification]
Run this command to verify:
ros2 topic list
Expected: You should see /my_topic in the list.
Validation Checklist
- [ ] Code compiles without errors (
colcon build) - [ ] Node runs and publishes data (
ros2 topic echo /my_topic) - [ ] RViz2 displays data correctly
Challenge (Optional)
[Extended task for advanced students, e.g., "Modify the node to publish at 100 Hz instead of 10 Hz"]
Troubleshooting
Problem: "Package not found"
Solution: Source your workspace (source install/setup.bash)
Problem: "Topic not visible"
Solution: Check if node is running (ros2 node list)
## Exercise Types
### 1. Thought Experiment (No Code)
**Format**: Conceptual questions to build intuition
**Example**: "List 5 tasks that require physical embodiment that an LLM alone cannot do"
### 2. Simulation Task (Gazebo/Isaac Sim)
**Format**: Code + Launch files + Gazebo world
**Example**: "Spawn a humanoid in Gazebo and make it walk forward 2 meters"
### 3. Hardware Integration (Jetson + Sensors)
**Format**: Deploy ROS 2 node to Jetson, read sensor data
**Example**: "Stream RealSense depth images to your workstation via Wi-Fi"
### 4. Capstone Project (Multi-Week)
**Format**: Complete system with milestones
**Example**: "Build an autonomous room-cleaning robot"
## Progressive Difficulty Curve
**Beginner** (Chapters 1-5):
- Copy-paste code examples
- Run pre-built packages
- Simple parameter changes
**Intermediate** (Chapters 6-15):
- Modify existing code
- Create new nodes
- Integrate multiple sensors
**Advanced** (Chapters 16-28):
- Design complete systems
- Optimize for hardware (Jetson)
- Implement novel algorithms
- Deploy to real robots
## Validation Standards
Every exercise must have:
1. **Clear Success Criteria** - "You should see X" or "The robot should do Y"
2. **Runnable Code** - Copy-paste should work without modification
3. **Hardware Note** - Explicitly state if Jetson/Robot required
4. **Time Estimate** - Realistic completion time for average student
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